International Journal of Aquaculture, 2016, Vol.6, No.19, 1
-
8
3
Farm sites with their peripheries (impact zones) and the whole area for 2 different regions within the bay were
considered as the subareas. Real-time datasets of TSM and SDD were obtained for 7 different days within the
same period. To create an NN algorithm, the full swaths of geo-located products (with 300 m resolution) from the
MERIS sensor aboard ENVISAT were used along with in situ data. Per the results, the author reported that a good
performance, with an accuracy of 97.46% for TSM and 99.58% for SDD were shown by the NN algorithm. The
2highest particle concentrations and lowest light penetration occurred in the spring and summer. Water circulation
patterns were identified as the major force determining the distribution and hence the source of particles and were
also applied to reflect the particle loads introduced by feeding activity performed in aquaculture facilities. The
influence of dissolved organic carbon to TSM and SDD indicates that the contribution of colored dissolved
organic matter is another important variable for effective monitoring of aquaculture activity in the bay.
In another study by Xu et al. (2014), the coastal aquaculture land use in Shandong Province was selected as the
research site. The authors employed the interactive visual interpretation method incorporating spatial and spectral
information from multi-source image objects was applied to Landsat TM/ETM+, CBERS-02B and HJ-1 images
which were acquired in the late 1980s, 2000, 2005 and 2010 covering the coastal area of Shandong Province was
used to help extract aquaculture land use information. In addition, the authors adopted different models including
the single land use dynamic index, the gravity center, the landscape fragmentation as well as multi-model analysis
of spatial information such as changes in the distribution area statistics to reveal the spatial patterns of Shandong
coastal aquaculture. From this study, coastal aquaculture in Shandong province had increased between 1980s and
2010 with slight variations in the period under consideration. It was revealed that there was a dynamic variation of
16. 95% between 1980s and 2000, however there was a gradual decrease after the year 2000. The authors further
documented that the changes of aquaculture land use indicate the spatial heterogeneity. The aquaculture area in
Dongying city keeps growing fast, followed by Binzhou city and Weihai city. But the growth rate in Qingdao city
and Weifang city has dropped after a period of increment. For nearly 30 years, the fragmentation degree of the
aquaculture area had increased by 4.5 times, and the gravity center of the aquaculture area had migrated to the
northwest. It was documented that the increased aquaculture land was mainly as a result of transformation from
the construction land, sea water bodies and the agriculture land whiles the loss in aquaculture land is mainly
turned into construction land and other forms of water bodies.
To assess the impact of aquaculture on mangroves, Pattanaik, and Prasad, (2011) undertook a study in Mahanadi
delta of Orissa, East coast of India an area noted for its distinctive mangrove ecosystem. In order to assess the
impacts aquaculture has on the study area, the authors employed satellite data for different periods of time
(Landsat MSS of 1973, Landsat TM of 1990 and IRS P6 LISS III of 2006). The study revealed that delta was
occupied by dense mangrove (12.6%), open mangrove (3.3%), aquaculture (12.9%) and agriculture (30.9%) in
2006. A loss of 2606 ha mangrove area and an increase of 3657 ha aquaculture area was observed from 1973 to
2006 clearly depicts the augment of aquaculture industry. From the revelations, the autors suggested that, regular
monitoring of the mangroves and effective implementation of coastal management laws be strictly undertaken to
prevent the further loss mangroves in Mahanadi delta.
2.2 Site selection for aquaculture
In aquaculture, site selection is a vital decision as it could determine the success of the industry. Site selection is a
key factor in any aquaculture operation, affecting both success and sustainability as well as solving conflicts
between different activities and making rational use of the land (Hossain and Das, 2010). It is therefore important
that the right site be selected in order to reap the full benefits of aquaculture. It has been documented that remote
sensing and GIS have been employed at different times and places in site selection for various aquaculture sectors.
These includes; clam culture in Florida (Arnold et al., 2000), brackish water aquaculture site selection in coastal
track of Cannanore (Gupta et al., 2001), scallop culture in Sungo Bay, China (Bacher et al., 2003), shrimp and
crab farming in Bangladesh (Salam et al., 2003), marine fish cage culture in Tenerife, Canary Islands (Pérez et al.,
2005), mangrove oyster raft culture in Margarita Island, Venezuela (Buitrago et al., 2005) suitable sites selection
